Carbon Dots: From Synthesis to Unraveling the Fluorescence Mechanism.

Carbon dots (CDs) being a new type of carbon-based nanomaterial have attracted intensive interest from researchers owing to their excellent biophysical properties. CDs are a class of fluorescent carbon nanomaterials that have emerged as a promising alternative to traditional quantum dots and organic dyes in applications including bioimaging, sensing, and optoelectronics. CDs possess unique optical properties, such as tunable emission, facile synthesis, and low toxicity, making them attractive for many applications in biology, medicine, and environmental areas. The synthesis of CDs is achievable by a variety of methods, including bottom-up and top-down approaches, involving the use of different carbon sources and surface functionalization strategies. However, understanding the fluorescence mechanism of CDs remains a challenge. Various mechanistic models have been proposed to explain their origin of luminescence. This review summarizes the recent developments in the synthesis and functionalization of CDs and provides an overview of the current understanding of the fluorescence mechanism.

Rapid and low-cost sampling for detection of airborne SARS-CoV-2 in dehumidifier condensate.

Airborne spread of coronavirus disease 2019 (COVID-19) by infectious aerosol is all but certain. However, easily implemented approaches to assess the actual environmental threat are currently unavailable. We present a simple approach with the potential to rapidly provide information about the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the atmosphere at any location. We used a portable dehumidifier as a readily available and affordable tool to collect airborne virus in the condensate. The dehumidifiers were deployed in selected locations of a hospital ward with patients reporting flu-like symptoms which could possibly be due to COVID-19 over three separate periods of one week. Samples were analyzed frequently for both virus envelope protein and SARS-CoV-2 RNA. In several samples across separate deployments, condensate from dehumidifiers tested positive for the presence of SARS-CoV-2 antigens as confirmed using two independent assays. RNA was detected, but not attributable to SARS-CoV-2. We verified the ability of the dehumidifier to rapidly collect aerosolized sodium chloride. Our results point to a facile pool testing method to sample air in any location in the world and assess the presence and concentration of an infectious agent to obtain quantitative risk assessment of exposure, designate zones as "hot spots" and minimize the need for individual testing which may often be time consuming, expensive, and laborious.

Brain Complexity in Children with Mild and Severe Autism Spectrum Disorders: Analysis of Multiscale Entropy in EEG.

Multiscale entropy (MSE) model quantifies the complexity of brain functions by measuring the entropy across multiple time-scales. Although MSE model has been applied in children with Autism spectrum disorders (ASD) in previous studies, they were limited to distinguish children with ASD from those normally developed without corresponding severity level of their autistic features. Therefore, we aims  to explore and to identify the MSE features and patterns in children with mild and severe ASD by using a high dense 64-channel array EEG system. This study is a cross-sectional study, where 36 children with ASD were recruited and classified into two groups: mild and severe ASD (18 children in each). Three calculated outcomes identified brain complexity of mild and severe ASD groups: averaged MSE values, MSE topographical cortical representation, and MSE curve plotting. Averaged MSE values of children with mild ASD were higher than averaged MSE value in children with severe ASD in right frontal (0.37 vs. 0.22, respectively, p = 0.022), right parietal (0.31 vs. 0.13, respectively, p = 0.017), left parietal (0.37 vs. 0.17, respectively, p = 0.018), and central cortical area (0.36 vs. 0.21, respectively, p = 0.026). In addition, children with mild ASD showed a clear and more increase in sample entropy values over increasing values of scale factors than children with severe ASD. Obtained data showed different brain complexity (MSE) features, values and topographical representations in children with mild ASD compared with those with severe ASD. As a result of this, MSE could serve as a sensitive method for identifying the severity level of ASD.

Classification of Normal, Ictal and Inter-ictal EEG via Direct Quadrature and Random Forest Tree.

This paper presents an accurate nonlinear classification method that can help physicians diagnose seizure in electroencephalographic (EEG) signal characterized by a disturbance in temporal and spectral content. This is accomplished by applying four steps. First, different EEG signals containing healthy, ictal and seizure-free (inter-ictal) activities are decomposed by empirical mode decomposition method. The instantaneous amplitudes and frequencies of resulted bands (intrinsic mode functions, IMF) are then tracked by the direct quadrature method (DQ). In contrast to other approaches, DQ cancels the effect of amplitude modulation on frequency calculation. The dissociation between instantaneous amplitude and frequency information is therefore fully achieved to avoid features confusion. Afterwards, the Shannon entropy values of both sets of instantaneous values (amplitudes and frequencies)-related to every IMF-are calculated. Finally, the obtained entropy values are classified by random forest tree. The proposed procedure yields 100% accuracy for (healthy)/(ictal) and 98.3-99.7% for (healthy)/(ictal)/(interictal) classification problems. The suggested method is hence robust, accurate, fast, user-friendly, data driven with open access interpretability.

Chiral Induction in 2D Borophene Nanoplatelets through Stereoselective Boron-Sulfur Conjugation.

Chirality is a structural metric that connects biological and abiological forms of matter. Although much progress has been made in understanding the chemistry and physics of chiral inorganic nanoparticles over the past decade, almost nothing is known about chiral two-dimensional (2D) borophene nanoplatelets and their influence on complex biological networks. Borophene's polymorphic nature, derived from the bonding configurations among boron atoms, distinguishes it from other 2D materials and allows for further customization of its material properties. In this study, we describe a synthetic methodology for producing chiral 2D borophene nanoplatelets applicable to a variety of structural polymorphs. Using this methodology, we demonstrate feasibility of top-down synthesis of chiral χ3 and ß12 phases of borophene nanoplatelets via interaction with chiral amino acids. The chiral nanoplatelets were physicochemically characterized extensively by various techniques. Results indicated that the thiol presenting amino acids, i.e., cysteine, coordinates with borophene in a site-selective manner, depending on its handedness through boron-sulfur conjugation. The observation has been validated by circular dichroism, X-ray photoelectron spectroscopy, and 11B NMR studies. To understand how chiral nanoplatelets interact with biological systems, mammalian cell lines were exposed to them. Results showed that the achiral as well as the left- and right-handed biomimetic χ3 and ß12 borophene nanoplatelets have distinct interaction with the cellular membrane, and their internalization pathway differs with their chirality. By engineering optical, physical, and chemical properties, these chiral 2D nanomaterials could be applied successfully to tuning complex biological events and find applications in photonics, sensing, catalysis, and biomedicine.

Binding-Induced Folding of DNA Oligonucleotides Targeted to the Nucleocapsid Gene Enables Electrochemical Sensing of SARS-CoV-2.

In the wake of the COVID-19 pandemic, millions of confirmed cases and deaths have been reported around the world. COVID-19 spread can be slowed and eventually stopped by a rapid test to diagnose positive cases of the disease on the spot. It is still important to test for COVID-19 quickly regardless of the availability of the vaccine. Using the binding-induced folding principle, we developed an electrochemical test for detecting SARS-CoV-2 with no RNA extraction or nucleic acid amplification. The test showed high sensitivity with a limit of detection of 2.5 copies/µL. An electrode mounted with a capture probe and a portable potentiostat are used to conduct the test. To target the N-gene of SARS-CoV-2, a highly specific oligo-capturing probe was used. Based on the binding-induced "folding" principle, the sensor detects binding between the oligo and RNA. When the target is absent, the capture probe tends to form a hairpin as a secondary structure, retaining the redox reporter close to the surface. This can be seen as a large anodic and cathodic peak current. When the target RNA is present, the hairpin structure will open to hybridize with its complementary sequence, causing the redox reporter to pull away from the electrode. Consequently, the anodic/cathodic peak currents are reduced, indicating the presence of the SARS-CoV-2 genetic material. Validation of the test performance was performed using 122 COVID-19 clinical samples (55 positives and 67 negatives) and benchmarked to the gold standard reverse transcription-polymerase chain reaction (RT-PCR) test. As a result of our test, the accuracy, sensitivity, and specificity have been measured at 98.4%, 98.2%, and 98.5%, respectively.

Diagnosis of COVID-19 with simultaneous accurate prediction of cardiac abnormalities from chest computed tomographic images.

COVID-19 has potential consequences on the pulmonary and cardiovascular health of millions of infected people worldwide. Chest computed tomographic (CT) imaging has remained the first line of diagnosis for individuals infected with SARS-CoV-2. However, differentiating COVID-19 from other types of pneumonia and predicting associated cardiovascular complications from the same chest-CT images have remained challenging. In this study, we have first used transfer learning method to distinguish COVID-19 from other pneumonia and healthy cases with 99.2% accuracy. Next, we have developed another CNN-based deep learning approach to automatically predict the risk of cardiovascular disease (CVD) in COVID-19 patients compared to the normal subjects with 97.97% accuracy. Our model was further validated against cardiac CT-based markers including cardiac thoracic ratio (CTR), pulmonary artery to aorta ratio (PA/A), and presence of calcified plaque. Thus, we successfully demonstrate that CT-based deep learning algorithms can be employed as a dual screening diagnostic tool to diagnose COVID-19 and differentiate it from other pneumonia, and also predicts CVD risk associated with COVID-19 infection.

Highly-Specific Single-Stranded Oligonucleotides and Functional Nanoprobes for Clinical Determination of Chlamydia Trachomatis and Neisseria Gonorrhoeae Infections.

Early detection of Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) is the key to controlling the spread of these bacterial infections. An important step in developing biosensors involves identifying reliable sensing probes against specific genetic targets for CT and NG. Here, the authors have designed single-stranded oligonucleotides (ssDNAs) targeting mutually conserved genetic regions of cryptic plasmid and chromosomal DNA of both CT and NG. The 5'- and 3'- ends of these ssDNAs are differentially functionalized with thiol groups and coupled with gold nanoparticles (AuNP) to develop absorbance-based assay. The AuNPs agglomerate selectively in the presence of its target DNA sequence and demonstrate a change in their surface plasmon resonance. The optimized assay is then used to detect both CT and NG DNA extracted from 60 anonymized clinical samples with a clinical sensitivity of ∼100%. The limit of detection of the assays are found to be 7 and 5 copies/µL for CT and NG respectively. Furthermore, it can successfully detect the DNA levels of these two bacteria without the need for DNA extraction and via a lateral flow-based platform. These assays thus hold the potential to be employed in clinics for rapid and efficient monitoring of sexually transmitted infections.

Ensemble and single-particle level fluorescent fine-tuning of carbon dots via positional changes of amines toward "supervised" oral microbiome sensing.

Significance: Carbon dots (CDs) have attracted a host of research interest in recent years mainly due to their unique photoluminescence (PL) properties that make them applicable in various biomedical areas, such as imaging and image-guided therapy. However, the real mechanism underneath the PL is a subject of wide controversy and can be investigated from various angles. Aim: Our work investigates the effect of the isomeric nitrogen position as the precursor in the synthesis of CDs by shedding light on their photophysical properties on the single particles and ensemble level. Approach: To this end, we adopted five isomers of diaminopyridine (DAP) and urea as the precursors and obtained CDs during a hydrothermal process. The various photophysical properties were further investigated in depth by mass spectroscopy. CD molecular frontier orbital analyses aided us in justifying the fluorescence emission profile on the bulk level as well as the charge transfer processes. As a result of the varying fluorescent responses, we indicate that these particles can be utilized for machine learning (ML)-driven sensitive detection of oral microbiota. The sensing results were further supported by density functional theoretical calculations and docking studies. Results: The generating isomers have a significant effect on the overall photophysical properties at the bulk/ensembled level. On the single-particle level, although some of the photophysical properties such as average intensity remained the same, the overall differences in brightness, photo-blinking frequency, and bleaching time between the five samples were conceived. The various photophysical properties could be explained based on the different chromophores formed during the synthesis. Overall, an array of CDs was demonstrated herein to achieve ∼100% separation efficacy in segregating a mixed oral microbiome culture in a rapid (<0.5 h), high-throughput manner with superior accuracy. Conclusions: We have indicated that the PL properties of CDs can be regulated by the precursors' isomeric position of nitrogen. We emancipated this difference in a rapid method relying on ML algorithms to segregate the dental bacterial species as biosensors.

Diagnostic Approaches For COVID-19: Lessons Learned and the Path Forward.

Coronavirus disease 2019 (COVID-19) is a transmitted respiratory disease caused by the infection of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although humankind has experienced several outbreaks of infectious diseases, the COVID-19 pandemic has the highest rate of infection and has had high levels of social and economic repercussions. The current COVID-19 pandemic has highlighted the limitations of existing virological tests, which have failed to be adopted at a rate to properly slow the rapid spread of SARS-CoV-2. Pandemic preparedness has developed as a focus of many governments around the world in the event of a future outbreak. Despite the largely widespread availability of vaccines, the importance of testing has not diminished to monitor the evolution of the virus and the resulting stages of the pandemic. Therefore, developing diagnostic technology that serves as a line of defense has become imperative. In particular, that test should satisfy three criteria to be widely adopted: simplicity, economic feasibility, and accessibility. At the heart of it all, it must enable early diagnosis in the course of infection to reduce spread. However, diagnostic manufacturers need guidance on the optimal characteristics of a virological test to ensure pandemic preparedness and to aid in the effective treatment of viral infections. Nanomaterials are a decisive element in developing COVID-19 diagnostic kits as well as a key contributor to enhance the performance of existing tests. Our objective is to develop a profile of the criteria that should be available in a platform as the target product. In this work, virus detection tests were evaluated from the perspective of the COVID-19 pandemic, and then we generalized the requirements to develop a target product profile for a platform for virus detection.

Monitoring the Viral Transmission of SARS-CoV-2 in Still Waterbodies Using a Lanthanide-Doped Carbon Nanoparticle-Based Sensor Array.

The latest epidemic of extremely infectious coronavirus disease 2019 (COVID-19) has created a significant public health concern. Despite substantial efforts to contain severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within a specific location, shortcomings in the surveillance of predominantly asymptomatic infections constrain attempts to identify the epidemiological spread of the virus. Continuous surveillance of wastewater streams, including sewage, offers opportunities to track the spread of SARS-CoV-2, which is believed to be found in fecal waste. To demonstrate the feasibility of SARS-CoV-2 detection in wastewater systems, we herein present a novel facilely constructed fluorescence sensing array based on a panel of three different lanthanide-doped carbon nanoparticles (LnCNPs). The differential fluorescence response pattern due to the counterion-ligand interactions allowed us to employ powerful pattern recognition to effectively detect SARS-CoV-2 and differentiate it from other viruses or bacteria. The sensor results were benchmarked to the gold standard RT-qPCR, and the sensor showed excellent sensitivity (1.5 copies/µL) and a short sample-to-results time of 15 min. This differential response of the sensor array was also explained from the differential mode of binding of the LnCNPs with the surface proteins of the studied bacteria and viruses. Therefore, the developed sensor array provides a cost-effective, community diagnostic tool that could be potentially used as a novel epidemiologic surveillance approach to mitigate the spread of COVID-19.

Single-gene diagnostic assay for rapid subclassification of basal like breast cancer with mRNA targeted antisense oligonucleotide capped molecular probe.

Basal-like breast cancers (BLBCs) represent a subset of ∼70% of triple negative breast cancers (TNBCs) and is significantly more aggressive than tumors of other molecular subtypes. The primary hurdle to develop an effective therapeutic possibility for BLBC lies in the failure to accurately classify this molecular subtype using typical histopathological practices. A clear clinical unmet need is therefore to develop a simple robust diagnostic assay for BLBC that can be made widely available to every pathology laboratory. Elevated expression of transcription factor Forkhead box C1 (FOXC1) has recently been reported as an important prognostic biomarker and functional regulator of BLBC. We herein developed a new nanotechnology-enabled molecular diagnostic assay that will target FOXC1 to directly classify BLBC types from tissue extracts. The molecular assay is comprised of unique antisense oligonucleotide (ASO) guided nanoprobe designed for specific targeting of FOXC1 mRNA. The developed assay has been optimized and validated analytically and demonstrated for its clinical applicability in a small cohort of breast cancer tissues. The significance of the results was further established and corroborated using FOXC1 protein-based ELISA, RT-PCR and fluorescence in-situ hybridization (FISH) assay by detecting the endogenous mRNAs at the ultrastructural level. The results reported herein could greatly improve accessibility of single gene based oncologic assay and help accelerate the accurate identification of this aggressive disease.

EMD-based analysis of complexity with dissociated EEG amplitude and frequency information: a data-driven robust tool -for Autism diagnosis- compared to multi-scale entropy approach.

OBJECTIVE: Autism spectrum disorder (ASD) is usually characterised by altered social skills, repetitive behaviours, and difficulties in verbal/nonverbal communication. It has been reported that electroencephalograms (EEGs) in ASD are characterised by atypical complexity. The most commonly applied method in studies of ASD EEG complexity is multiscale entropy (MSE), where the sample entropy is evaluated across several scales. However, the accuracy of MSE-based classifications between ASD and neurotypical EEG activities is poor owing to several shortcomings in scale extraction and length, the overlap between amplitude and frequency information, and sensitivity to frequency. The present study proposes a novel, nonlinear, non-stationary, adaptive, data-driven, and accurate method for the classification of ASD and neurotypical groups based on EEG complexity and entropy without the shortcomings of MSE. APPROACH: The proposed method is as follows: (a) each ASD and neurotypical EEG (122 subjects × 64 channels) is decomposed using empirical mode decomposition (EMD) to obtain the intrinsic components (intrinsic mode functions). (b) The extracted components are normalised through the direct quadrature procedure. (c) The Hilbert transforms of the components are computed. (d) The analytic counterparts of components (and normalised components) are found. (e) The instantaneous frequency function of each analytic normalised component is calculated. (f) The instantaneous amplitude function of each analytic component is calculated. (g) The Shannon entropy values of the instantaneous frequency and amplitude vectors are computed. (h) The entropy values are classified using a neural network (NN). (i) The achieved accuracy is compared to that obtained with MSE-based classification. (j) The consistency of the results of entropy 3D mapping with clinical data is assessed. MAIN RESULTS: The results demonstrate that the proposed method outperforms MSE (accuracy: 66.4%), with an accuracy of 93.5%. Moreover, the entropy 3D mapping results are more consistent with the available clinical data regarding brain topography in ASD. SIGNIFICANCE: This study presents a more robust alternative to MSE, which can be used for accurate classification of ASD/neurotypical as well as for the examination of EEG entropy across brain zones in ASD.

Small Molecule NIR-II Dyes for Switchable Photoluminescence via Host -Guest Complexation and Supramolecular Assembly with Carbon Dots.

Small molecular NIR-II dyes are highly desirable for various biomedical applications. However, NIR-II probes are still limited due to the complex synthetic processes and inadequate availability of fluorescent core. Herein, the design and synthesis of three small molecular NIR-II dyes are reported. These dyes can be excited at 850-915 nm and emitted at 1280-1290 nm with a large stokes shift (≈375 nm). Experimental and computational results indicate a 2:1 preferable host-guest assembly between the cucurbit[8]uril (CB) and dye molecules. Interestingly, the dyes when self-assembled in presence of CB leads to the formation of nanocubes (≈200 nm) and exhibits marked enhancement in fluorescence emission intensity (Switch-On). However, the addition of red carbon dots (rCDots, ≈10 nm) quenches the fluorescence of these host-guest complexes (Switch-Off) providing flexibility in the user-defined tuning of photoluminescence. The turn-ON complex found to have comparable quantum yield to the commercially available near-infrared fluorophore, IR-26. The aqueous dispersibility, cellular and blood compatibility, and NIR-II bioimaging capability of the inclusion complexes is also explored. Thus, a switchable fluorescence behavior, driven by host-guest complexation and supramolecular self-assembly, is demonstrated here for three new NIR-II dyes.

N-gene-complementary antisense-oligonucleotide directed molecular aggregation of dual-colour carbon dots, leading to efficient fluorometric sensing of SARS-COV-2 RNA.

The early stages of the COVID-19 pandemic punctuated the need for rapid, mass testing for early detection of viral infection. Carbon dots are easily synthesized, cost-effective fluorescent nanoparticles whose surface functionalities enable facile conjugation with biorecognition elements suitable for  molecular detection of viral RNA. Herein, we report that a pair of complementary antisense oligonucleotide (ASO) sequences can lead to a highly specific molecular aggregation of dual colour carbon dots (CDs) in the presence of SARS-CoV-2 RNA. The nanoprobes used ASOs highly specific to the N-gene of SARS-COV-2. When the ASOs are conjugated to blue and yellow citric acid-derived CDs, the combination of the ASO-CD pairs facilitates aggregation-induced emission enhancement (AIEE) of the measured fluorescence after hybridization with SARS-CoV-2 RNA. We found the sensor capable of differentiating between MERS-CoV and SARS-CoV-2 samples and was found to have a limit of detection of 81 copies per µL. Additionally, we used dialysis to demonstrate that the change in emission upon aggregation is dependent on the compositional heterogeneity of the conjugated-carbon dot mixture.

A rapid RNA extraction-free lateral flow assay for molecular point-of-care detection of SARS-CoV-2 augmented by chemical probes.

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the major shortcoming of healthcare systems globally in their inability to diagnose the disease rapidly and accurately. At present, the molecular approaches for diagnosing COVID-19 primarily use reverse transcriptase polymerase chain reaction (RT-PCR) to create and amplify cDNA from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA. Although molecular tests are reported to be specific, false negatives are quite common. Furthermore, literally all these tests require a step involving RNA isolation which does not make them point-of-care (POC) in the true sense. Here, we report a lateral flow strip-based RNA extraction and amplification-free nucleic acid test (NAT) for rapid diagnosis of positive COVID-19 cases at POC. The assay uses highly specific 6-carboxyfluorescein (6-FAM) and biotin labeled antisense oligonucleotides (ASOs) as probes those are designed to target N-gene sequence of SARS-CoV-2. Additionally, we utilized cysteamine capped gold-nanoparticles (Cyst-AuNPs) to augment the signal further for enhanced sensitivity. Without any large-stationary equipment and highly trained staffers, the entire sample-to-answer approach in our case would take less than 30 min from a patient swab sample collection to final diagnostic result. Moreover, when evaluated with 60 clinical samples and verified with an FDA-approved TaqPath RT-PCR kit for COVID-19 diagnosis, the assay obtained almost 99.99% accuracy and specificity. We anticipate that the newly established low-cost amplification-free detection of SARS-CoV-2 RNA will aid in the development of a platform technology for rapid and POC diagnosis of COVID-19 and other pathogens.

In Situ Surface-Directed Assembly of 2D Metal Nanoplatelets for Drug-Free Treatment of Antibiotic-Resistant Bacteria.

The development of antibiotic resistance among bacterial strains is a major global public health concern. To address this, drug-free antibacterial approaches are needed. Copper surfaces have long been known for their antibacterial properties. In this work, a one-step surface modification technique is used to assemble 2D copper chloride nanoplatelets directly onto copper surfaces such as copper tape, transmission electron microscopy (TEM) grids, electrodes, and granules. The nanoplatelets are formed using copper ions from the copper surfaces, enabling their direct assembly onto these surfaces in a one-step process that does not require separate nanoparticle synthesis. The synthesis of the nanoplatelets is confirmed with TEM, scanning electron microscopy, energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FT-IR). Antibacterial properties of the Cu nanoplatelets are demonstrated in multidrug-resistant (MDR) Escherichia coli, MDR Acinetobacter baumannii, MDR Staphylococcus aureus, E. coli, and Streptococcus mutans. Nanoplatelets lead to a marked improvement in antibacterial properties compared to the copper surfaces alone, affecting bacterial cell morphology, preventing bacterial cell division, reducing their viability, damaging bacterial DNA, and altering protein expression. This work presents a robust method to directly assemble copper nanoplatelets onto any copper surface to imbue it with improved antibacterial properties.

Probing the mutation independent interaction of DNA probes with SARS-CoV-2 variants through a combination of surface-enhanced Raman scattering and machine learning.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolution has been characterized by the emergence of sets of mutations impacting the virus characteristics, such as transmissibility and antigenicity, presumably in response to the changing immune profile of the human population. The presence of mutations in the SARS-CoV-2 virus can potentially impact therapeutic and diagnostic test performances. We design and develop here a unique set of DNA probes i.e., antisense oligonucleotides (ASOs) which can interact with genetic sequences of the virus irrespective of its ongoing mutations. The probes, developed herein, target a specific segment of the nucleocapsid phosphoprotein (N) gene of SARS-CoV-2 with high binding efficiency which do not mutate among the known variants. Further probing into the interaction profile of the ASOs reveals that the ASO-RNA hybridization remains unaltered even for a hypothetical single point mutation at the target RNA site and diminished only in case of the hypothetical double or triple point mutations. The mechanism of interaction among the ASOs and SARS-CoV-2 RNA is then explored with a combination of surface-enhanced Raman scattering (SERS) and machine learning techniques. It has been observed that the technique, described herein, could efficiently discriminate between clinically positive and negative samples with ∼100% sensitivity and ∼90% specificity up to 63 copies/mL of SARS-CoV-2 RNA concentration. Thus, this study establishes N gene targeted ASOs as the fundamental machinery to efficiently detect all the current SARS-CoV-2 variants regardless of their mutations.

Hyperspectral Mapping for the Detection of SARS-CoV-2 Using Nanomolecular Probes with Yoctomole Sensitivity.

Efficient monitoring of SARS-CoV-2 outbreak requires the use of a sensitive and rapid diagnostic test. Although SARS-CoV-2 RNA can be detected by RT-qPCR, the molecular-level quantification of the viral load is still challenging, time-consuming, and labor-intensive. Here, we report an ultrasensitive hyperspectral sensor (HyperSENSE) based on hafnium nanoparticles (HfNPs) for specific detection of COVID-19 causative virus, SARS-CoV-2. Density functional theoretical calculations reveal that HfNPs exhibit higher changes in their absorption wavelength and light scattering when bound to their target SARS-CoV-2 RNA sequence relative to the gold nanoparticles. The assay has a turnaround time of a few seconds and has a limit of detection in the yoctomolar range, which is 1 000 000-fold times higher than the currently available COVID-19 tests. We demonstrated in ∼100 COVID-19 clinical samples that the assay is highly sensitive and has a specificity of 100%. We also show that HyperSENSE can rapidly detect other viruses such as influenza A H1N1. The outstanding sensitivity indicates the potential of the current biosensor in detecting the prevailing presymptomatic and asymptomatic COVID-19 cases. Thus, integrating hyperspectral imaging with nanomaterials establishes a diagnostic platform for ultrasensitive detection of COVID-19 that can potentially be applied to any emerging infectious pathogen.

RNA-extraction-free nano-amplified colorimetric test for point-of-care clinical diagnosis of COVID-19.

The global pandemic of coronavirus disease 2019 (COVID-19) highlights the shortcomings of the current testing paradigm for viral disease diagnostics. Here, we report a stepwise protocol for an RNA-extraction-free nano-amplified colorimetric test for rapid and naked-eye molecular diagnosis of COVID-19. The test employs a unique dual-prong approach that integrates nucleic acid (NA) amplification and plasmonic sensing for point-of-care detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with a sample-to-assay response time of <1 h. The RNA-extraction-free nano-amplified colorimetric test utilizes plasmonic gold nanoparticles capped with antisense oligonucleotides (ASOs) as a colorimetric reporter to detect the amplified nucleic acid from the COVID-19 causative virus, SARS-CoV-2. The ASOs are specific for the SARS-CoV-2 N-gene, and binding of the ASOs to their target sequence results in the aggregation of the plasmonic gold nanoparticles. This highly specific agglomeration step leads to a change in the plasmonic response of the nanoparticles. Furthermore, when tested using clinical samples, the accuracy, sensitivity and specificity of the test were found to be >98.4%, >96.6% and 100%, respectively, with a detection limit of 10 copies/µL. The test can easily be adapted to diagnose other viral infections with a simple modification of the ASOs and primer sequences. It also provides a low-cost, rapid approach requiring minimal instrumentation that can be used as a screening tool for the diagnosis of COVID-19 at point-of-care settings in resource-poor situations. The colorimetric readout of the test can even be monitored using a handheld optical reader to obtain a quantitative response. Therefore, we anticipate that this protocol will be widely useful for the development of biosensors for the molecular diagnostics of COVID-19 and other infectious diseases.